~IERDIE EKSEMPLAAR MAG ONDER
University of the Free State
Faculty of Natural and Agricultural Sciences Department of Plant Sciences
Plant Breeding
Bloemfontein, Republic of South Africa, 2003
Genetic variability and combining ability for
quality
parameters
in
Ethiopian
wheat
cultivars
by
Tadesse Dessalegn Woldegiorgis
A dissertation submitted in the fulfillment of the
requirements for the degree, of·
"
-s" '. '\~
,:" .'
, ',',
Philosophiae Doctor
Major Promoter:
Prof C.S. van Deventer (ph.D)
Co-Promotor
: Prof. M. T. Labuschagne (ph.D)
To my mother Sahlemariam Ayele and in
memory
of
my
Father,
Dessalegn
Woldegiorgis
Dedication
To my wife Yehuwalashet Feleke and our
children, Barnabas, Kale and Kaleh
"The roots of education
are bitter, but the fruit is
sweet"
-Aristotle
lV
DECLARATION
I hereby declare that this dissertation is submitted to the department of plant breeding at the University of the Free State in compliance with the requirements for the degree Philosophiae Doctor is my own exertion and has not been previously submitted to any other University. I concede that the University of the Free State has the copyright of this dissertation.
Signature:
Table of contents
Declaration iv
Table of contents
v
List of figures vii
List of tables viii
Abbreviations x
Acknowledgement xii
Chapter 1 Introduction 1
Chapter 2 Literature Review
3
2.1 Technological quality of wheat 3
2.2 Polymorphism and functional role of storage proteins 9
2.3 Combining ability of quality traits 19
2.4 References 21
Chapter 3 Bread making quality of Ethiopian wheat cultivars and prediction
using direct and indirect quality traits 34
3.1 Abstract 34
3.2 Introduction 34
3.3 Material and methods 36
3.4 Results and discussion 37
3.5 Conclusion , 50
3.6 References 50
Chapter 4 Allelic variation of HMW glutenin subunits in Ethiopian bread
wheat cultivars and their quality scores 54
4.1 Abstract 54
4.2 Introduction 54
4.3 Material and methods 56
4.4 Results and discussion 58
4.5 Conclusion 64
4.6 References 64
Chapter 5 Combining ability analysis for quality traits in crosses of bread wheat (Triticum aestivum L.) cultivars tested in northwestern Ethiopia 67
5.1 Abstract 67
5.2 Introduction 67
5.3 Material and methods 69
5.4 Results and discussion 70
5.5 Conclusion 80
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Chapter 6 Variability for quality traits and bread making in Ethiopian durum
wheat cultivars and advanced lines 84
6.1 Abstract 84
6.2 Introduction 84
6.3 Material and methods 86
6.4 Results and discussion 87
6.5 Conclusion 97
6.6 References 98
Chapter 7 B-LMW glutenins and ')'-gliadin compositions of Ethiopian durum
wheat genotypes and their association with some quality traits 101
7.1 Abstract 101
7.2 Introduction 101
7.3 Material and methods 102
7.4 Results and discussion 103
7.5 Conclusion 108
7.6 References 109
Chapter 8 Summary and recommendations 111
List of figures
Figure 1 Mixograph measurements 7
Figure 2 Comparison of the traditional (functional) and new (molecular)
classification of gluten proteins 10
Figure 3 Chromosomal location of genes coding for gluten proteins 11
Figure 4 Allelic variation of HMW glutenin subunits at three gene loci based on SOS-PAGE fractionation and relationship to bread making
quality 12
Relationship of SOSS alone with LFV (Model I) 46
Relationship of FPC alone with MOT (Model 111) 47
Correlation of measured and calculated LFV in Model 1 47
FPC vs LFV relationship at Bainsvlei 47
SOS-PAGE patterns of HMW of some lines and cultivars 59
Mixograph development time (MOT) of 10 banding patterns 63
Gluten strength (W) values of 10 banding patterns 63
Relationship between SOSS and LFV at higher protein
environment 95
Actual and predicted values of MOT using selected variables
in the model 95
SOS-PAGE subunit patterns of HMW and B-LMW glutenins 105
SOS-PAGE patterns of gliadin in some of the genotypes 106
Figure 5 Figure
6
Figure 7 Figure8
Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15List of tables
Table 1 Methods, units and abbreviations of measurements of quality traits 37 Table 2 Mean of quality traits of selected cultivars/lines tested at the three
environments 39
Table 3 Mean and ranges of quality traits for selected lines tested
at three environments 40
Table 4 Mean squares of quality parameters tested at three environments 41 Table 5 Variance components and repeatability of quality parameters
tested at three environments 42
Table 6 Phenotypic and genotypic correlations between direct and indirect
parameters for quality traits tested a three environments 56
Table 7 Variables, regression coefficients and R2values of prediction
equations for quality traits 45
Table 8 Actual, predicted and percent errors of LFV and MOT using
the three regression models 48
Table 9 List of cultivars and advanced lines used 57
Table 10 HMW quality scoring methods based on SOS-sedimentation
test and alveograph gluten strength 58
Table 11 Frequency of each allele (subunit) at different loci
(Glu-A1, Glu-B1, Glu-01)
59
Table 12 Jointly occurring subunits of Glu-B1 and Glu-01 60
Table 13 Mean of quality traits and Glu-1 scores of the banding patterns
at the three loci 60
Table 14 Mean squares of varieties and HMW banding patterns 61
Table 15 Mean separation of the subunit combinations 63
Table 16 ANOVA giving expectation of mean squares 70
Table 17 Mean yields and quality parameters of parents and their F1's
across environments 71
Table 18 Mean squares for yield and quality traits at individual and pooled
environment(s) 72
Table 19 Mean squares of combining abilities of separate and combined
environments 72
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Table 21 General and specific combining ability effect of parents and their
hybrids in a combined analysis 77
Table 22 Narrow sense heritability estimates 78
Table 23 Methods, units and abbreviations of measurements of quality traits 87 Table 24 Mean of yield and quality traits of genotypes grown at Motta 88 Table 25 Mean of yield and quality traits of genotypes grown at Adet 89 Table 26 Mean of cultivars/lines for yield and quality traits studied
across environments 91
Table 27 Analysis of variance, variance components and repeatability
of quality traits 92
Table 28 Phenotypic correlation of the studied traits 93
Table 29 Regression coefficients, R2and tests of multicolinearity 94
Table 30 Methods, units and abbreviations of measurements of quality traits 103 Table 31 Patterns and allelic compositions of HMW, B-LMW and
gliadins of Ethiopian genotypes and standards 103
Table 32 Frequency of glutenin and gliadin subunits composition 104
Table 33 Mean of some quality traits of studied lines and cultivars
across two environments 107
Table 34 Mean values of quality traits for glutenin and gliadin patterns 107
ABBREVIATIONS
AACC '" American Association of Cereal Chemists
A-PAGE Acid Polyacrylamide Gel Electrophoresis
AWRC Alkaline Water Retention Capacity
BFL Y Break Flour Yield
call Covariance
CV Coefficient of Variation
Env Environment
FABS Farinograph Water Absorption
FCL Flour Color
FLN Falling Number
FLY Flour Yield
FPC Flour Protein Content
GCA General Combining Ability
GIi Gliadin
GLM General Linear Model
GILl Glutenin
GLUT Wet Gluten
GYI) Grain Yield
B Heterosis
h2" Narrow sense heritability
HLW Hectoliter Weight
HMW-GS High Molecular Weight Glutenin Subunit
HP Better Parent
L. '" Extensibility
LFV Bread Loaf Volume
LMW-GS Low Molecular Weight Glutenin Subunits
LSD Least Significant Differences
MA Mid-parent Advantage
MI)T. Mixograph Development Time
Me Error mean square
Mg
Mean square of genotypes,
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T.~9.N~
MP Mid-parents
MS Mean Square
NCSS Number Cruncher Statistical System
P Tenacity
R2 " Coefficient of determination
RCB Randomized Complete Block
rg Genotypic correlations
RP-HPLC Reverse Phase High Performance Liquid
Chromatography
SAS Statistical Analysis System
SeA '" Specific Combining Ability
SOS-PAGE Sodium Dodecyl Sulphate-Polyacrylamide Gel
Electrophoresis
SDSS Sodium Dodecyl Sulphate Sedimentation
SE Standard Error
SKCS Single Kernel Characteristics System
SKDM SKCS-Seed Diameter
SKHI. " " SKCS- Hardness Index
SKWT SKCS-Seed Weight
TG W 1000 Grains Weight
VIF Variance Inflation Factor
VK " Vitreous Kemels
W Alveograph dough (gluten) strength
a
2 Variance) E'
cr
e ... . . . .. rror vanance) G . .
cr
g . . . enotypic vananceo',
Genotype by environment interaction variancerjJ2 '" Variance due to fixed effect
) Add' . "
0'A ...•..••....••••.•.•••. itrve genetic vanance
d
AE Additive by environmental variance) D" .
0'D . . . .. emmanee genetic vanance
ACKNOWLEDGEMENT
I am highly indebted to record my earnest gratitude for the following:
Q Prof. C.S. van Deventer, my major promoter, for his thorough close follow-up,
encouragement and keen guidance to equip me with theoretical background accompanied with his unforgettable instructive discussions of future practical applications using his ample academic experience
e Prof. M.T. Labuschagne, my eo-promotor, for her commitment, invaluable
intellectual advices and wholehearted supervisions during all moments of my work
oDr. H. Maartens for creating an excellent laboratory environment, instructing me all the steps of laboratory analysis and helping me in the understanding of the results
• Ms. S. Geldenhuys for providing me excellent administrative support
throughout my study
G Ms. Chrissie Miles and her quality laboratory team at ARC-Small Grain Institute,
South Africa, for analyzing the grain quality of my wheat samples
o My colleagues in the breeding division and the center management at Adet agricultural research center, Ethiopia, for rendering me the necessary help to run my field experiments
oOr. Bedada Girma and Mr. Bemnet Gashabeza, national wheat research
coordinators, for their cooperation and providing me bread and durum wheat germplasm
o Prof. J.M. Carrillo at university of Madrid, Spain, for his durum wheat standards;
Dr. G.Humphreys at Agriculture and Agri-food, Winnipeg, Canada, for his bread wheat standards; and Prof. M.S.Kang Louisiana State University, USA, for
giving me DIALLEL-SAS analysis software; Mr. O.G. Tanner of CIMMYT
, ~.C;!5N9.It{~.~P.9.s¥.~N!.
Cl Adet Research Center of Amhara Regional Agricultural Research Institute
(ARARI) for nominating me for this opportunity and Agricultural Research Training Project (ARTP) of Ethiopian Agricultural Research Organization (EARO) for financing my scholarship
o My wife, Yehuwalashet Feleke, for her encouragement, prayers and
unprecedented moral support during my study which I might not succeed with out it. I love you; appreciate your understanding, strength and courage to overcome the hard task of nursing our very young children in good and bad times while I was long time away from you
Every step in my life including completion of this undertaking is by the will of my Lord, God.
Chapter 1
Introduction
Wheat belongs to the tribe Triticeae of the grass family Poaceae and genus Triticum which
form a polyploid series with the basic chromosome number x=7 (Moris and Sears, 1967). The
bread (Triticum aestivum L. ssp. aestivum) and durum (Triticum turgidum L. (ThelI.) ssp.
durum (Desf.) Husn.) are the most important polyploid wheat species containing three
(AABBDD, 2n=6x=42) and two (AABB, 2n=4x=28) related genomes, respectively. The main
theory on the origin of the hexaploid wheat is that it evolved from the recurrent hybridizations
between a cultivated tetraploid (AABB, probably Tturgidum) and the wild diploid (DD),
Aegilops squarrosa (Mcfadden and Sears, 1946; Bonjean and Angus, 2001). Bread wheat is
unique because its flour alone has the ability to form dough that exhibits the rheological
properties required for the production of leavened bread, other foods such as flat bread,
biscuits and noodles (Gainibelli et al, 2001). Durum wheat is milled into semolina and has
larger kernel size, hardness and golden amber calor. Itis widely known to produce superior
pasta products and couscous, medium-dense breads and other foods specific to certain regions
(Pella et aI, 2002). Wheat is grown on an area of over 200 million hectares and is now yielding
almost 600 million tones annually (Marshall et al, 2001).
The genus Triticum in Ethiopia is represented by seven species (Vavilov, 1929) i.e., T.
dicoccum, T durum, T .turgidum, T polonicum, T aestivum, T compactum and T pyrimidale.
Bread and durum are the two most widely grown important species. Bread wheat is an
introduced crop, relatively unknown, in Ethiopia as opposed to durum wheat which is
indigenous to the country (Hailu, 1991). The country is considered as a primary center of
diversity for tetraploid wheats (Vavilov, 1931) and currently it has the greatest diversity.
Ethiopia is the largest wheat producer in sub-Saharan Africa (Hailu, 1991) producing about
1.125 million tons occupying 750,000 hectares having aSS % level of self-sufficiency (Tanner
and Mwangi, 1991; Payne et al, 2001). Wheat, both durum and bread, ranks 4th in area of
production (1,139,720 ha) after tef, maize and sorghum; 3rd in total production (1,571,169
tons) after tef and maize; and 2nd in productivity (l.38 tons ha") after maize (eSA, 2001).
Other than pan bread, wheat is used for making injera (pancake type bread), local bread,
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The improvement of wheat since its commencement prior to the 1930's (Tessema, 1988; Hailu, 1991) has focused on improving yield and disease resistance. Since recently, the selection of varieties for higher yield preceded that of quality. The cultivar release process requires meeting agronomic superiority with relatively little emphasis on inherent quality characteristics. Currently, due to the emerging agro-industries using wheat as a raw material, industrial quality of wheat has become important (Bechere et aI., 2000) and an effective strategy for wheat (bread and durum) quality improvement is required. The unsatisfactory supplies of wheat grain in terms of quality and quantity have forced some industries to import wheat from Australia and Canada (Tadesse, unpublished survey information, 2001). There is a need to strengthen the quality breeding through further exploring the genetic and environmental aspects affecting wheat quality under the wheat growing conditions of the county to meet consumer and processor demands for quality of end use products. The objectives of this study were to:
o Examine the bread making quality of widely grown commercial wheat cultivars and
advanced breeding lines, identify the major contributing factors of quality under the growing conditions of northwestern Ethiopia, develop prediction models using indirect and direct measurements of quality and recommend the minimum required quality traits for possible use in the wheat breeding program of northwestern Ethiopia.
o investigate the high molecular weight, B-low molecular weight glutenins and )"-gliadin composition of Ethiopian bread and durum wheat genotypes and their associations with some physical quality traits
• study the combining ability, relative importance of additive and non-additive gene effects, genetic association and inheritance of grain and flour quality traits tested at different environments in northwestern Ethiopia
Chapter 2
Literature review
2.1
Technological quality of wheat
Wheat quality can not be expressed in terms of a single property (Finney et aI., 1987). Test
weight, lOOO-kernel weight, and flour yield are frequently used as indicators of milling quality.
Measurements of baking quality include wheat or flour protein concentration, mixing time,
water absorption, loaf volume, and crumb grain and color. Several of these traits have
moderate to high heritability (Braaten et al., 1962; Halloran, 1975; Loffler and Busch, 1982).
The most important food use of wheat is in the manufacture of flour for bread making,
biscuits, pastry products (Finney et aI., 1987) and breakfast cereals. Other uses of wheat
include separation of its flour into starch and gluten used for industrial products, as a feed and
ethanol production (Orth and Shellenbereger, 1988). Thus, the basic definition of wheat
quality usually varies from one class of wheat to another. The quality of soft red or soft white
wheat cultivars is its suitability for the production of cakes, cookies, and crackers. The quality
of durum wheat is its suitability for semolina and macaroni production and of hard red winter
and spring wheat is its specific properties that determine suitability for hard wheat milling and
bread production. Thus, quality of any kind of wheat depends on several milling, chemical,
baking, processing, and physical dough characteristics. End-use quality of any wheat genotype
is the summation of effects of soil, climate, and seed stock on the wheat plant and the kernel
components (Haunold et al.; 1962a, Finney et al., 1987).
Bread-making quality is an important but complex character of bread wheat (Pomeranz, 1988).
Bread-making technology varies around the world depending on the consumer demands, the
baker and technological differences (MacRitchie, 1984) and it is very difficult to formulate
applicable criteria for bread-making quality. However, laboratories always resort to the use of
several direct and indirect quality traits which include test weight, Zeleny or
SDS-sedimentation test, Pelshenke, mixograph, farinograph, alveograph, falling number, micro
baking, hardness, protein content etc. and different researchers have recommended various
traits for quality evaluations.
In their study of six baking methods, Baker et al. (1971) suggested that a quality screening
.9_1:1.~?!p~
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~nF.lJ.~ll!.~.f~.~Y.I.~w.development time and some indication of the factors that affect the gassing power. Branlard et al (1991) have compared 125 European cultivars using 17 technological test giving 46 technological parameters during three years in 18 locations. The correlation studies revealed that flour yield, test weight and falling number were generally weakly correlated to the other tests; protein content affected many tests; Zeleny, micro-baking, mixograph, bread-making and Pelshenke were strongly correlated (in descending order) to the other tests. The parameters giving the greatest number of significant correlations were (in descending order) modified Zeleny, alveograph strength, and mixograph height at seven min, farina graph weakening, and micro-baking. Fowler and De La Roche (1975) studied 28 different wheat kernel and flower measurements and recommended the use of kernel hardness, protein quantity and rate of dough development to provide the basic information required for estimation of the bread and/or pastry potential of a cultivar. O'Brien and Ronaids (1987) suggested that the most effective early generation selection for quality is achieved when wheats are assessed using a regime of tests that estimate grain hardness, flour protein content and some measure of potential dough strength.
Kernel hardness is very often used as an important criterion to classify wheat quality (Aamodt and Torrie, 1935; Symes, 1961; Meppelink, 1974) and related to milling and flour quality. Wheats are generally divided into two classes, hard and soft. Hard wheat requires more force to fracture kernels, maintain a larger particle size, it passes through sieves more easily, and has more damaged starch in the resultant flour. Endosperm texture is variable, and environmental factors exert modifying effects (MacRitchie, 1980; Mattem, 1988; Anjum and Walker, 1991). Protein and moisture content are important, and factors such as interaction between protein and starch, minerals, and moisture within the endosperm matrix play important roles. Bran may also affect hardness (Green way, 1969). A vitreous (translucent or horn like) appearance is generally associated with hardness and high protein content, and opaqueness (mealyness or flouryness) with softness and low protein content (Hoseney, 1986). Hard wheats generally have high protein and tend to be vitreous, but the cause for hardness and vitreousness are different. Vitreousness is related to a lack of air spaces between granules of starch, whereas hardness relates to protein-starch bond strength and protein matrix continuity between granules. Air spaces make the opaque grain less dense and are formed during grain drying. The protein shrinks, ruptures and leaves air spaces upon drying. In vitreous kernels, the protein shrinks but remains intact (Hoseney, 1986). Low protein soft wheats are opaque or mealy, but at higher protein, the grain is or can be translucent or vitreous. This change in appearance
CHAPTER 2 LITERATURE REVIEW
...
Test weight of normal (unshrivelled and undamaged) soft wheat grain is the combination of
two factors: the density of the kernel itself and a random volume occupied by the grain
(packing efficiency). It is also associated with shape of the grain (Yamazaki and Briggle,
1969). Kernel density reflects the environment in which the grain was grown and is dependent
on the volume of the air in the grain as well as protein content to some extent, which also
affects grain appearance. Low protein grain (mealy in appearance) has more or larger air
pockets than those of relatively high protein kernels (vitreous in appearance, which may have
no air pockets). Presumably, in the low protein dry wheat there is insufficient protoplasmic
(protein) material to fill the interstices between starch granules in the cells. Test weight
decreases with kernel deformation, especially by shriveling, and in these cases, there is an
obvious increase in the ratio of bran to endosperm and concomitant yield loss.
Weight of 1000 grains can give an indication of flour yield on the basis that large, well filled,
dense grain will contain a greater amount of endosperm compared with bran. However,
correlations with flour yield are not particularly high. In durum wheat, however, kernel size,
and therefore 1000 grain weight, is considered the best index for potential semolina yield per
unit of grain (Matsuo and Dexter, 1980).
Break flour is the portion of the kernel endosperm of flour fineness obtained without crushing
or reduction in the milling operation. Soft wheats fracture into significantly smaller particles
than hard wheats, reflected in the greater quantity of break flour in milling (Yamazaki and
Denelson, 1983). Flour yield has been shown to be a cultivar trait (Yamazaki and Andrews,
1982) and can range from 72-79 % on a products basis. Flour yield potential is better
expressed when the experimental milling technique is optimized for each wheat being tested,
rather than subjecting grains differing in milling response to a uniform procedure. Hard wheat
of good milling quality should have nomlal bolting or sifting properties and therefore should
be neither unusually hard nor soft. If, in addition, the wheat gives a normal yield of flour with
a normal quantity of ash, almost invariably it will be suitable as good milling hard wheat.
Wheat that is too hard usually requires more power and more than the normal number of break
and reduction operations. The flour from such wheat usually will have relatively high ash
content (Finney et al., 1987).
The amount of variation in loaf volume that can be explained by protein content varied from
1-86 % (Weegels et aI., 1996). Improved bread making can be achieved by increasing protein
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determined by the composition of the storage proteins mainly dependent on genotype. Protein
content is strongly influenced by environment and growing conditions (Graybosch et al.,
1996). The glutenin content of flour could explain variation in loaf volume as well as, or better
than, protein content and could be even more important than protein content in determining
bread-making quality. O'Brien and Ronaids (1984) found a significant negative correlation
between grain yield and flour protein content. However, grain yield was not significantly
correlated with other quality measures, indicating that high yielding, good quality wheats
could be obtained from the population.
Sedimentation test is the measure of protein aggregative ability and effectively provides a
semi-quantitative determination of the amount of glutenin macropolymer based on the
flocculation of polymeric glutenin in SDS/lactic acid solution (Axford et aI., 1979; Weegels et
al., 1996). There is an excellent correlation between the amount of gel protein and
SDS-sedimentation volume (SDSS) and it indicates the bread-making quality of flours in a rapid
and simple way. Good bread-making quality is associated with large SDS volume. Axford et
al. (1979) have shown that sedimentation volume of 56 flours of 10 varieties correlated
strongly with the volume of loaves from the same flours both by a long fermentation baking
process and a mechanical development process. High correlations were confirmed between
the amount of SDS unextractable protein and the Chopin Alveograph Wand Pvalues
(Dachkevitch and Autran, 1989), and SDSS to protein content and loaf volume (de Villiers
and Laubscher, 1995). Lorenzo and Kronstad (1987) found that SDSS values were highly
influenced by variation in protein content of the grain as opposed to Blackman and Gill (1979)
and Presten et al. (1982) who found that SDSS values were not affected by variation in the
protein content in the grain. Nitrogen fertilization and locality affected SDSS volume as well
as the protein content and bread volume thereby affecting the relationship between them (de
Villiers and Laubscher, 1995).
Two important bread-making properties, mixing time and mixing tolerance are objectively
determined from the mixogram (Figure 1). Both the quality and quantity of proteins affect the
mixing (physical dough) properties of bread wheat flours (Finney and Shogren, 1972).
Mixograph mixing time is more highly correlated with experimental bake mixing time than is
Farinograph mixing time (Miller et al., 1956; Shellenberger et al., 1970). In general, the longer
the mixing time is, the better the mixing tolerance. A medium to medium-long mixing
CHAPTER 2 LITERA TURE REVIEW ...
extensible than dough having a longer mixing time of 2.5 to 3 min. In general, as mixing time
increases, dough extensibility decreases and dough stability and elasticity increases (Grass et
al, 2001).
rn(lir:imum oondwidth
//~oo WId!11otpeok lesl~anoe
~.__»-:" ...r 40 m
-
l_r) '(Jj <1'1 II rêststOn.ce brool:.dO'WI1o
Time (seconds)
Figure 1. Mixograph measurements. The x-axis tracks the time since the start of mixing and
the y-axis measures the instantaneous levels of power required to mix the dough. The width of
the trace reflects the repeated stretching and rupture of the dough as it is mixed (Source: Grasa
et al., 2001)
As protein content increases within a cultivar, water absorption increases (Finney, 1945). The
water absorption at a given protein level varies between cultivars indicating it is a function of
quantity and quality of wheat flour proteins. Correlations between baking data and mixograph
characteristics were substantiated (Dong et al., 1992; Khatkar et al., 1996), and proved to be a
powerful tool to investigate indices of bread making quality (Martinant et al., 1998), and
mixogrpph characterstics are used as an official physical test in many countries. Dong et al.
(1992) found significant correlations between protein concentration and both ioaf volume and
absorption and between mixing tolerance and crumb grain score. No association was found
between total protein content and mixing properties. High molecular weight glutenin subunits
(HMW -GS) 5+ 10 had the most consistently positive effect on most of the quality
measurements. They concluded that using biochemical methods to identify wheat genotypes
with specific HMW glutenin and gliadin composition in parental and early generation
.9.I:I.~f.!.;R
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~nf:~~TI!.~.;.~gy'I.;w.Alveograph is widely used to determine the bread-making quality of wheat. It measures dough resistance, elasticity and protein strength of bread wheats. Yamamotto et al (1996) after investigation of four classes of soft wheats recommended the use of the alveograph and mixograph as useful tools for evaluation of soft wheat quality for cake and cookie baking. Farinograph is the most widely used physical dough testing instrument. It may be used to estimate absorption, optimum mixing time, and mixing tolerance, provided the necessary correlations have been established (Shellenberger et aI., 1970).
Loaf volume is a function of both the quantity and quality of flour proteins (Finney et aI., 1987). A flour of good quality for bread-making should have a high water absorption, a medium-long mixing requirement, a small to medium oxidation requirement, satisfactory mixing tolerance and dough handling properties, and good loaf volume potential (considering protein content) (Finney et aI., 1987). Also, it should yield a loaf that has good internal crumb grain and color. Loaf volume at the 13 % protein level increases as mixing time increases up to about 3 min. Beyond 3 min, loaf volume is approximately constant with increasing mixing time. The lowest loaf volumes for mixing time greater than 3 min are considered to be barely satisfactory. Thus, mixing time or requirement obtained from the mixogram is a reliable index of loaf volume potential and protein quality, when selecting cultivars that have mixing requirements of about 3 min or greater (Finney et aI., 1985).
The end-use quality of any wheat genotype can vary tremendously depending on the geographical production environment, soil N availability, temperature during grain filling, distribution of rainfall, and late season frosts (Haunold et aI., 1962b; Faridi and Finley, 1989; Randam and Moll, 1990; Johnson and Marten, 1987; Graybosch et al., 1996). Peterson et al (1992) found that genotype, environment, and interaction effects significantly influence the variation in all quality parameters and variances of quality characteristics associated with environmental effects were generally larger than those for genetic factors. It is known that grain yield and protein concentration often are negatively correlated in cereal crops, especially when soiI nitrogen is limiting (Haunold et aI., 1962b). Cox et al. (1989) after examining the changes in quality of releases from 1874-1988 concluded that deterioration in quality may be caused by nongenetic factors such as changes in the environment, milling practices, commercial baking methods and formulations, or some combinations of these factors.
In
a genotype by environment study of soft wheats, Basset et al. (1989) found significant effects of cultivar and environment in flour yield, percent flour protein, hardness and sedimentation,.9.f:I.~f.!.~R
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interactions were small, but significant. Among the variance components, years contributed
most to total variance for protein, sedimentation and A WRC. The year by site component was
greatest for flour yield, cookie diameter and hardness. Relatively large cultivar by environment
components for cookie diameter, hardness, and A WRC required their evaluation across
multiple site years.
2.2
Polymorphism and functional role of storage proteins
The unique properties of the wheat gram reside primarily in the gluten forming storage
proteins of its endosperm which gives its viscoelastic properties. The essence of elasticity is
that, following extension, a restoring force exists which tends to return the material to its
original dimensions. For most traditional uses, wheat quality derives mainly from two
interrelated characteristics: grain hardness and "protein quality". Quality is determined by the
molecular structure of the storage proteins of wheat, that in turn, controls the interactions of
the proteins during the bread making process (Payne, 1987; Bushuk, 1998; Gainibelli et al.,
200 I).
Based on their sequential extraction and differential solubility, Osborne (1907) classified
wheat proteins into four different groups, albumins (soluble in water and dilute buffers),
globulins (not soluble in water but soluble in saline solutions), prolamins (which are soluble
in 70-90 % ethanol), and glutel ins (which are soluble in dilute acid or alkali). Later on, Ch en
and Bushuk (1970) added a fifth fraction by dividing glutenin into two fractions: one soluble
in dilute acetic acid (O.OSM) and other insoluble in this solvent. However, each of these
fractions is a complex mixture of different polypeptides and that these polypeptides overlap
in their solubilities particularly the gliadin and glutenin proteins.
After the reduction of disulfide bonds, all gluten proteins are soluble in 70 % ethanol or
other alcohol such as n-propanol as individual polypeptide chains (Kreis et aI., 1985). They
have thus been classified as prolamins due to the existence of close similarity in structure
between low molecular weight glutenin subunits (LMW-GS) and gliadins (Shewry et al.,
1986). All gluten proteins are high in proline and glutamine contents, the name prolamins
being derived from the combined names of these amino acids. Within this group, further
differences between them are based on biochemical characteristics: sulfur-rich, sulfur-poor,
.9.I:I.~?!.~R.? ~~!~FJ.~ll!.~g.~.~y.I.~w.
proteins), the glutenins are multi-chained structures of poly pep tides that are held together by
disulfide bonds. The very high molecular weight of these polymeric structures is responsible
for their partial insolubility and for their distinct contribution to functionality compared- with
that of the gliadins.
. .
: Wheat gluten proteins
... ···1···· Menomeric Aggregative glutenins
I
gliadinsmHHHH1H'
: : HM\'\Ii i
sub units HM\'\I prolanuns S-poor prolamiris S-rich prolaminsFigure 2. Comparison of the traditional (functional) and new (molecular) classification of
gluten proteins (Shewry et aI., 1986)
Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) is the procedure
most widely used to separate the reduced subunits of glutenin. In SDS-PAGE, SDS masks
protein charge, and thus separation depends only on size. This shows two groups of bands,
which have been called the high molecular weight (HMW, 80,000-130,000 Da) and low
molecular weight (LMW, 10,000-70,000 Da) subunits (Bietz and Wall, 1972; Payne et al.,
1980; Jackson et aI., 1983). True estimates calculated from derived amino acid sequences
indicate lower molecular weights for HMW-GS (Anderson et aI., 1989; Anderson and Green,
1989).
According to the scheme of Pay ne et al. (1979), HMW-GS were termed A subunits, LMW-GS
were further broken down into two groups, B-subunits (slower moving), and C-subunits (faster
moving) distantly related to 't: and o-gliadins. Finally, the D-group, also belonging to the
LMW-GS group, is highly acidic and related to o-gliadins (Jacks on et aI., 1983; Masci et aI.,
CHAPTER 2 LITERATURE REVIEW
, ,
The HMW glutenin subunits of wheat protein are quantitatively minor but functionally
important group of gluten proteins in the process of bread making (Tatham and Shewry, 1985;
Shewry et al., 1992). They are encoded at the Glu-I loci on the long arm of the group 1
chromosome lA, lB, and ID at Glu-Al , Glu-Bl and Glu-Dl loci, respectively (Payne 1987;
Shewry et al., 1992; Figure 3). Each locus consists of two genes encoding a HMW x-type
subunit and a HMW y-type subunit (Payne et al., 1981). Most alleles at Glu-Bl and Glu-Dl
encode two high molecular subunits of glutenin named as x-type (lower mobility) and y-type
(higher mobility) in SDS-PAGE (Rogers et al., 1991); both types of subunits are important in
influencing bread making quality.
Long arm Short arm
Glu-l Gli-l/Glu-3
lA---I---o---I----
IB---I---o---I----
ID---I---o---I----Gli-2o---I----6A
o---I----6B
o---I----6D
Figure 3. Chromosomal location of genes coding for gluten proteins (MacRitchie and
Lafiandra, 2001)
Appreciable polymorphism was found in the number and mobility of HMW -glutenin subunits
in both bread wheats (Lawrence and Shepherd, 1980; Payne et al., 1980) and pasta wheats
(Waines and Payne, 1987; Branlard et al., 1989). The polymorphism provides a basis for the
correlation of specific alleles with differences in bread making performance. Payne and
Lawrence (1983) summarized the range ofalleles at the Glu-I loci as three allelic forms (one
of which is null or silent) at the Glu-LA, 11 alleles (involving 14 different polypeptides) at the
Glu-LB, and six alleles (eight different polypeptides) at the Glu-Dl (Figure 4) which also
provides the chromosomal locations of the genes. Since the publication of this catalog of
alleles at Glu- 1 loci, more alleles that are novel have been identified (McIntosh et al., 1994;
CHAPTER 2 LITERATURE REVIEW ... , 10-2 1-2
.
en
1? 18_7 Glu-A1 CO "0 18-8 C CO 10-12li
~ ~ ~ >£. !1 10-2 'ë :J[
''']
_,
.0 18-7 -21 :J 11- - -7-7 ~_'J_14 Cf)=
-168 19-'5 > 18-8 18 - -8 Glu-B1 -22 ~ 10-12 i > !;b ~ 9>• >jj ::x: ~ a h 1 k = Ol -2.2 c: 'e a. 10-2 _5--2-3-4 -2 -2 en Q) Cf) 18-7 Glu-D1 Q) c 18-8 E -II U 10-12 -1(~]2 _'2_12 -'O_,2.
~>!z~>£ .! 1a
[?!::'t t·,if! -not tested
Quality
Figure 4. Allelic variation HMW glutenin subunits at three gene loci based on SDS-PAGE fractionation and relationship to bread making quality (Payne et al., 1984a). Lowercase letters refer to allele designations of Pay ne and Lawrence (1983) (Source: Gianibelli et al., 2001)
Bread wheat could, in theory, contain six different HMW glutenin subunits, but due to the "silencing" of some of these genes, most common wheat cultivars possess three to five HMW-GS (one to three subunits in durum wheats). Thus, all hexaploid wheats contain at least the
l Bx, 1Dx, and 1Dy subunits, while some cultivars also contain 1By and lAx subunits (Gainibelli et al., 2001). It appears that the gene encoding the lAy subunit is always silent. However, some bread wheats with six HMW-GS have been reported (Johansson et al., 1993; Margiotta et al., 1996) and lAy subunits in A-genome diploid species (Waines and Payne, 1987) have been published. A particular feature of the HMW subunits (Shewry et al., 1989) is that they contain very large amounts of glutamine (35 mol %) and significant amounts of glycine (20 mol %) and proline (10 mol %). They are linear proteins, which consist ofC and N terminal, which are largely alpha helical, separated by long domains of repeat sequences. The evidence obtained from spectroscopic results has lead to the suggestion that hydrogen bonding between the repeat regions of the HMW subunits is responsible for the elasticity of the gluten (Belton, 1999). The length and nature of the repeat region in the HMW subunits will play a role in the viscoelastic properties.
The relationship between HMW subunits and bread making quality were studied as the presence and absence of subunits (Payneet al., 1984a; Payne et al., 1987; Pogna et al., 1987;
l
CHAPTER 2 LITERATURE REVIEW
...
Dardevet, 1985; Ng and Bushuk, 1988) and the additivity or combined role of HMW and
LMW glutenin subunits in improving bread making quality (Payne et al., 1987; Gupta et al.,
1989; Shewry et al., 1992). Other grain components, such as lipids and carbohydrates also
affect bread making quality, possibly by interacting with the gluten proteins.
Genetic studies (Payne et al., 1981) and studies correlating HMW glutenin composition with
known quality characteristics of released varieties (Payne et al., 1987) have established the
presence of subunits with both positive (5+10) and negative (2+12) effects on bread making
quality (Graybosch, 1992). Other allelic variant pairs had similar results: Glu-BJ sub units
17+ 18 (strong) versus subunits 20x+20y (weak). These differences in dough strength were due
to differences in molecular size of glutenin polymers deduced from solubility measurements
(Gupta and MacRitchie, 1994). The origins of the allelic differences have not been established.
However, in comparing 5+ 10 and 2+ 12, an extra cysteine residue in Dx5 was suggested as a
possible explanation (Anderson and Green 1989; Kasarda, 1999). Recent advances in micro
scale mixing and protein-engineering systems have proved to be valuable in elucidating
structure and functional relationship in gluten proteins (Bekes et al., 1998). Branlard and
Dardevet (1985) reported that the alveograph parameters W (gluten strength) and P (tenacity),
and the Zeleny sedimentation value are correlated positively with subunits 7+9 and 5+ 10, and
negatively with bands 2+ 12, whereas subunit 1 is correlated to Wand subunits 2
*
and 17+ 18with G (extensibility). In general, a Null at Glu-AJ locus, subunit 4+8 encoded at Glu-BJ and
2+ 12 at Glu-DJ are negatively related to the quality parameters (Weegels et al., 1996).
Quantity of the glutenin macro-polymer content (gel protein) is statistically related to bread
making quality and dough properties than individual subunits (Weegels et al., 1996).
However, it is apparent that wheat flours from cultivars with HMW glutenin subunits 5+10
have larger glutenin macropolymer content. These subunits are indirectly related to good
bread-making quality. Glutenin subunits or alleles could be used, however, as indicators of
quality for breeding purposes, when only small amounts of material are available and fast
quality prediction is necessary.
Some cultivars have better quality than expected on the basis of their HMW subunit
composition, while the quality of others is unexpectedly low. In many cases, this is related to
the presence of translocated lBR/IRS translocation. However, available evidence indicates
that the HMW glutamines play an important role and directly limit quality in some cultivars.
CHAPTER 2 LITERATURE REVIEW
...
conditions under which the varieties were bred. The patterns of high HMW glutenin subunits
amongst varieties with superior bread making quality showed few differences from from those
of bread making varieties of lower quality.
A scormg system for HMW-GS has been developed (Payne et aI., 1987) using major
subunits encoded at the A, B, and D genome in which individual subunit pairs are graded
with numbers based on bread making quality evaluations. A given cultivar can then be
assigned a Glu-i score, which is the sum of the contributions of each of the three HMW -GS
loci. Many breeding programs have characterized the HMW-GS composition of their
breeding and released lines/cultivars (Lawrence, 1986; Payne, 1987; Rogers et aI., 1989;
Morguno et al., 1990; Lukow, 1991; Lookhart et al., 1993; Igrejas et al., 1999; Nakamura,
2001) in relation to end-use quality and used it as a screening test to ensure that good bread
making alleles (1, 2*, 7+9, 7+8, 5+10) are incorporated into new cultivars (Lukow, 1991).
The HMW-GS score has more influence in some sets of wheats than in others (MacRitchie
et aI., 1990) and lines with poor banding combinations (2+12) produced a relatively high
volume (Lorenzo and Kronstad; 1987, Bedê et ai, 1995). This is likely to be due to the
complex interaction of factors that define wheat quality. These factors, in which HMW-GS
have a major role, also include LMW -GS, gliadins, and abiotic stresses. Nevertheless,
reference to HMW -GS composition has proved val uable in the segregation of lines in the
process of breeding for specific quality targets (Weegels et aI., 1996; Cornish et aI., 1999).
Studies indicated that variation in HMW subunits of genotypes accounts 20-60 % of the
variation in bread making quality (Payne et aI., 1987; Lukow et aI., 1989; Rogers et aI., 1989;
Kolster et aI., 1991). When protein content was below 9.2 %, no effect of allelic variation at
the Glu-D i locus was present (Kolster et al., 1991). Epistatic effects between Glu- i loci also
contributed to the variation in loaf volume of the lines; for example, the effect of allelic
variation at Glu-Al and Glu-Bl depend on the allele present at Glu-Dl. Branlard (1987) who
studied genotypes with a protein content varying from 10 to 19 % found effects of HMW
alleles on the bread making quality between 10 % and 15 %protein and no effects when the
protein exceeds 15 %. Therefore, the variation in HMW allele composition depends on the
protein content of the flour used in the baking test.
,9.J:I.~?T.~R
.4
~nf:~~ll!.~.~.~.~~l.~w.electrophoresis analysis (SDS-PAGE) of HMW-GS was a reliable indicator of loaf volume at
specific protein levels. Bands 5+ 10 contributed from the D genome, with either bands 1 or 2
*
from the A genome and bands 7 and 8 or 17 and 18 coded by the B genome were con-elated
with high volume. HMW glutenin banding patterns were independent of environmental factors
and could help in identifying good bread making quality in low protein environments but this
technique might not be as reliable in continental climates where loaf volume can be a function
of high protein content. The values of SDSS discriminated between wheat lines giving high or
low loaf volume, but SDSS values were found to be dependent upon variation in protein
content for the experimental material used.
Brunori et al. (1989) studied relationships of dough strength and mixing stability in relation to
flour protein content, glutenin/gliadin ratio, and high molecular weight subunits in bread wheat
progenies. They concluded that genotype selection based on HMW subunits of glutenins
would have a beneficial effect on dough strength (W). High W could be associated with a high
glutenin/gliadin ratio as well as with the presence of specific HMW subunits of glutenin. They
also suggested a reasonable breeding objective could be the development of wheat varieties
with medium expression of gluten quality sufficient for bread making purposes. Varieties of
this type may be expected to maintain a practically constant bread making quality through the
years, especially in respect to the expression of a balanced PIL ratio.
Kolster et al. (1991) studied 226 lines, which were not selected for quality, and found that 20
% of the total variation in loaf volume was accounted for by the variation in HMW glutenin
subunits. Most important was the allelic variation at the Glu-Dl locus, the glutenin allele
encoding the subunit 5+10 was superior to its allelic counterpart, encoding 2+12. The
difference in average of loaf volume between groups of lines containing 5+10 or 2+ 12 was
negatively correlated with protein content of the flours. When the protein was below 9.2 %, no
effect of allelic variation at the Glu-Dllocus was present.
Campbell et al. (1987) used a wide range of materials from very different breeding programs
chosen on the basis of agronomic characters rather than grain quality, to overcome previous
reports by others for small scale quality tests and for different sets of wheats. In their
biochemical study of HMW, using Payne and Lawrence's (1983) classification, consistent
prominence of Glu 5+ 10 (producing strong wheat) and Glu 2+ 12 (associate with poor quality)
was found consistent with previous studies (Payne et aI., 1981; Payne and Lawrence, 1983).
,9.
I:I.J??m~
.?
~~!~JJ.J?ll!.~.f~.~y.l.~w.durums. This probably explains why HMW glutenin subunits have not been associated with
dough properties in durum wheats (Du Cross, 1987). In the same study, they reported the
strong association of gliadins (58, 59, 60 67) with dough resistance. The associations have a
strong genetic basis and are thus valuable in breeding.
It was suggested (Payne et al., 1981), that bringing together those subunits which correlate
strongly with bread-making quality by conventional breeding using the SDS-sedimentation
test as a primary screen and SDS-PAGE as a secondary screen to test the desired subunits
provided the effects of the good-quality subunits from each of the alleles are additive then new
varieties with improved quality should result from this approach.
The determination of HMW glutenin proteins by SDS-PAGE has been evaluated as a
screening test for Canadian bread wheat (Lukow, 1991). The extensive use of the back
crossing method in western Canadian programs largely ensures that good bread making
alleles (1, 2*, 7+9, 7+8, 5+10) are incorporated in new cultivars. Therefore, SDS-PAGE
screening of early generation lines is a useful technique.
The LMW-GS (B-, C-, and D-subunits) represents about one-third of the total seed protein
and :::::60%of total glutenins (Bietz and Wall, 1973). Advances in characterization ofLMW
proteins are enhanced by recent SDS-PAGE (Singh et al., 1991a; Gupta and MacRitchie,
1991), RP-HPLC and capillary electrophoresis (Bean and Lookhart, 2000). Gupta and
Shepherd (1990) extensively described the major LMW-GS for bread wheat (T aestivum L.)
based on genetic analysis and on the chromosomal location of the encoding genes and by
Jackson et al. (1996). Nieto- Taladriz et al. (1997) described the allelic variation of the
B-type LMW-GS in durum wheat (T durum). Both systems are based on the relative
electrophoretic mobility of subunits in SDS-PAGE. The LMW -GS are controlled by genes at
the Glu-A3, Glu-B3, and Glu-D3 loci on the short arms of chromosome lAS, IBS, and IDS,
respectively. On the basis of screening a collection of 222 hexaploid wheats from 32
countries, Gupta and Shepherd (1990) detected 20 different band patterns (LMW-GS
blocks), six for the Glu-A3 locus, nine for the Glu-B3 locus, and five for the Glu-D3 locus.
Recently, two new LMW-GS with molecular weights of :::::30-31,000 Da (Glu-D410cus) and
32,000 Da (Glu-D5 locus) were reported (Sreeramulu and Singh, 1997). Some cultivars do
not exhibit any LMW-GS encoded by Glu-A3. On the other hand, there is extensive
CHAPTER 2 LITERA TURE REVIEW
...
LMW-GS are controlled by genes on group-6 chromosomes (Lewet al., 1992; Gupta and
Shepherd, 1993).
Close linkage between the Glu-3 loci encoding LMW-GS and the Gli-I loci has been
reported (Payne et al., 1984b; Singh and Shepherd, 1984, 1988; Pogna et al., 1990). The
Gli-I multigene loci encode )'- and o-gliadins and some ,6-gliadins at the distal ends of the short
arms of Chromosomes lA, 1B, and ID. This close linkage (estimated as 2cM between
Glu-B3 and GIi-B I on the short arm of chromosome 1B in both bread and durum wheat) is useful
for identifying the Glu-B3 alleles and some of the Glu-D3 alleles in breeding programs.
Because the gliadin composition can be screened more readily than specific LMW-GS, the
gliadins are potentially useful as indicators ofLMW-GS alleles (Singh et al., 1991b; Jackson
et aI., 1996). Earlier studies identified the presence of )'-gliadins 45 and 42 as reliable
markers for good and poor pasta quality, respectively (Damidaux et aI., 1978; Kosmolak et
aI., 1980). The effect of )'-gliadins on pasta quality was related to genetic linkages with
LMW-GS (Payne et al., 1984b).
The allelic variation at the LMW-GS loci is associated with significant differences in dough
quality in bread (Gupta et aI., 1989, Gupta and MacRitche, 1994) and durum wheat (Pogna
et aI., 1990; Ruiz and Carrillo, 1993). LMW-GS have the ability to form large aggregates
that are related to dough strength. Payne et al. (1984 b) were the first workers to associate
LMW-GS with quality characters of tetraploid wheat. A preliminary study ranking
LMW-GS alleles in order of quality also has been reported by Gupta et al. (1989), Cornish (1995),
and Cornish et al. (1999). However, it has been suggested that the effect of these alleles on
quality will be more accurately assessed if they are considered in conjunction with the
HMW-GS (Gupta and MacRitche, 1994).
Gliadins are heterogeneous mixtures of single-chained polypeptides, which are, in their
native state, soluble in 70 % aqueous alcohol.
In
accordance with their mobility inacid-PAGE (A-PAGE), they are divided into four groups: (Y.- (fastest mobility), ,6-, )'-, and
w-gliadins (slowest mobility). The molecular weight range is ::::::30,000 to 75,000 Da. Using
one-dimensional electrophoresis, gliadins of a single wheat grain can be separated into 20-25
components (Bushuk and Zillman, 1978; Autran et aI., 1979; Wrigley et al., 1982;
Metakovsky et al., 1984). Two-dimensional electrophoresis allows better separation with a
resolution of up to 50 components (Wrigley, 1970; Payne et aI., 1982; Pogna et aI., 1990).
.9.I:I.~?!.;R
.?
~rff:~~l'!.~.~.~.~YI.;w.identification in hexaploid and tetraploid wheats. The )'-gliadins differ from (X- and ,6-gliadins
in the amount of aspartic acid, proline, methionine, tyrosine, phenilalanine, and tryptophan
(Bietz et aI., 1977). The w-gliadins differ in amino acid composition from other gliadins and
do not have cysteine. The w-gliadins are characterized by high levels of glutamine
(+glutamate) (40-50 mol %), proline (20-30 mol %), and phenylalanine (7-9 mol %), which
represent> 80 % of the total amino acid residues (Tatham and Shewry, 1995). All gliadins
are low in the ionic amino acids (histidine, arginine, lysine, and free carboxylic groups of
aspartic acid and glutamic acid). Glutamic and aspartic acids exist almost entirely as amides.
Also, gliadins can be classified according to their N-terminal amino acid sequence.
Based on electrophoretic mobility, the nomenclature of gliadins uses the letters cx,,6, )' and w
to identify four different electrophoretic zones in acid-PAGE. An approach developed by
Bushuk and Sapirstein (1991), based on previous work (Sapirstein and Bushuk, 1985),
defines three arbitrary gliadin bands (40.4, 53.2, 68.6) of a reference wheat cultivar
(Neepawa) as limits for the determination of the four groups: w
«
40.4), )' (40.4-53.2), ,6(53.2-68.6), and (X(> 68.6). Nevertheless, genetic (Payne et aI., 1982) and chemical studies
involving amino acid analyses and N terminal sequences (Bietz et aI., 1977; Kasarda et aI,
1983) suggested that the gliadins can be arranged into three major groups of
cxJ,6-, )'-,
andw-gliadins.
The genetic system of gliadin nomenclature uses two types of allelic designations. In one
case, each gliadin component is identified by the chromosome on which its encoding gene is
located. In the second, groups of genetically linked gliadin components are designated by an
allelic block identified by the chromosomes and block letters; this is the designation
currently used (Wrigley et aI., 1996).
Genes coding these proteins are located on the short arms of group 1 and 6 chromosomes
(Wrigley and Shepherd, 1973; Brown and Flavell, 1981). They are tightly linked genes
located at three homologous loci of the group 1 chromosome: Gii-Al, Gii-Bl, and Gii-Dl
and group 6 chromosomes: GIi-A2, GIi-B2, and GIi-D2 loci. Gli-l genes code for all the
w-and most of the )'-gliadins while Gli-2 genes code for all the (X-, most of the ,6-, and some of
the )'-gliadins. Each cluster codes for a number of poly pep tides (a block) that is inherited as a
Mendelian character, and multiple allelism has been established in both GIi-1 and Gli-2 loci
9.1:f.~f.!.;[!
.?
~rr~~.~llJ.~.;.~.;Y.l.;WContemporary work has. indicated that the distribution of loci controlling
w-
and ')I-gliadinson group 1 chromosomes is more complex than originally supposed (Redaelli et aI., 1992;
Nieto-Taladriz and Carrillo, 1996; Rodriguez-Quijano and Carrillo, 1996). Some researchers
have questioned the earlier conclusion of Metakovsky et al (1986), suggesting that gliadins
are controlled by gene clusters at the Gii-I, Gli-Z loci, and some other single genes separated
from them. There is, thus, the concept that the genetics of gliadins should be modified to
allow for the possibility that whole clusters of genes have been duplicated, as is now being
revealed at the Gii-A3 and GIi-B3 loci (Nieto-Taladriz and Carrillo, 1996). Allelic variants of
the blocks differ in the number, mobility, and intensity of their components and can be
characterized through A-PAGE or even SDS-PAGE. Metakovsky and eo-workers studied
this group of proteins in detail. The scope of their work covered the allelic composition of
gl iadins from hexaploid wheat, tetraploid wheat, and diploid species related to wheat
(Metakovsky et al., 1984, 1986; Metakovsky and Iakobashvili, 1990; Metakovsky and
Baboev, 1992).
Gliadins are generally considered to contribute to the viscosity and extensibility of gluten.
Although some authors have associated specific gliadin alleles with bread making quality, it
is now accepted that these proteins may not have a direct effect on wheat quality in terms of
dough strength (Gainibelli et al., 2001). This role may instead be due to the LMW-GS
because of their tight genetic linkage to the gliadins. The low lysine content (0.5 mol %) of
the gliadins is a major negative factor affecting the nutritional quality of the wheat proteins.
2.3
Combining ability of quality traits
Wheat quality depends on many genetic and non-genetic factors. Understanding of the
inheritance of wheat quality traits, joint inheritance and their association with the environment
is vital (Baker and Sutherland, 1991) to improve wheat quality. Combining ability analysis of
diallel crosses is useful to understand the nature of gene action involved in determining
quantitative traits (Griffing, 1956a,b; Baker, 1978) and identify crosses with superior
performance for use in a practical breeding program. An estimation of additive and
non-additive genetic components can be made from the experimental material in terms of general
(GCA) and specific (SCA) combining ability variances. The GCA effects represent the fixable
component of genetic variance (Sprague, 1966). Parents with good combining ability for a
.9.J:l.J!.f.!.~R
.?
~n~~J!.TI!.~.~.~.~~t_~w.character. The SeA represents a non- fixable component of genetic variation, related to heterosis. Therefore, combining ability indicates the value of varieties as parents, identifies satisfactory hybrids and offers an indication of the mode of inheritance for the traits studied.
Quality traits are many and their inheritance is complex and shows a considerable degree of genetic variation. It has been found that progress in breeding for grain yield has been slower in the high quality bread making varieties (Shebeski, 1966; Bingham and Lupton, 1987). This may partly be attributed to the logistical difficulties of selecting for the many additional independently inherited characters of a top quality variety (Bingham et al., 1981). Edwards (1987b) and Virmani and Edwards (1983) have observed that GCA is of greater importance than SCA in wheat, although the latter appears to be more important in space plantings. Many reports suggest that GCA is the principal source of improved grain yield in hybrids, as in line varieties (Borghi et al., 1989; Morgan et al., 1989; Pickett, 1993) with small contribution from SCA. Rodriguez et al. (1967) reported high-test weights in 45 hybrids where one parent was a poor performer in this respect. Perenzin et al. (1987) and Edwards (1987a) reported mean test weights that equal or are above the means of parents. Crosses between parents of different texture have been found to produce variable results (Rodriguez et al., 1967; Edwards, 1987b). Studies on flour extraction levels in wheat crosses vary from no heterosis (Bitzer and Fu, 1972), intermediate to parents (Edwards, 1987b) and high parent or higher levels than parents.
There are several quality tests, which examine the rheological and baking properties of flour (Kent, 1983; Blackman and Payne, 1987). The SDS sedimentation test, which uses sodium dodecyl sulphate as a solution, is widely used to indicate protein quality. Brears and Bingham (1989) reported that most hybrids were intermediate in sedimentation. SDS sedimentation volume correlated with dough strength measures, and it was suggested as a useful test to select for dough strength (O'Brien et al., 1987). Quantity of protein is largely the result of environment and has been shown to be under polygenic control (Haunold et al., 1962a; Stuber et al., 1962). Protein levels in hybrids were shown to lie between parents, fall near to the lower parent and lower than the high parent. It appears that higher values can be achieved by selection of parents. Gyawali et al. (1966) found significant specific combining ability effects for grain yield, kernel weight but not for flour yield. GCA effects were significant for grain yield, kernel weight, pearling index and flour yield and they concluded interclass diversity is not necessary for heterosis. Mou et al. (1994) found negative correlation between kernel weight and protein concentration in two years and heritability estimates of 0.79 for kernel weight. Matuz et al. (1993), in crosses of Hungarian and North American winter wheat
.9.1:1.~?T.;~
.?
~~!f8.~ll!H.f~.;y'I_;w.varieties, found negative heterosis or intermediate inheritance for water absorption,
development time, stability of dough, loaf volume and protein content. Borghi et al. (1987)
suggested that genes for inferior dough quality acted dominant. He found crosses to be lower
in dough quality than parents, sometimes approaching the lower parent. Edwards (1987a)
reported that hybrids were generally intermediate in dough characteristics although there were
exceptions in both directions. Most researchers have concluded that breeding for bread
making quality is possible although it will be necessary to select parents carefully to achieve
this (Shebeski, 1966; Rodriquez et al., 1967; Wilson, 1968; Edwards, 1987b; Borghi et al.,
1987). According to review of Picket (1993), it appears that bread wheat quality is cross
specific.
2.4
References
Aamodt, O.S. and Torrie, lH., 1935. Studies on the inheritance of and the relation between
kemel texture and protein content in several spring wheat crosses. Can. J. Res. Sect. 202.
Anderson, O. D, Green, F.
c.,
Yip, R. E., Halford, N. G.,Shewry, P. R. and Malpica-Romero,1. M., 1989. Nucleotide sequences of the two high-molecular-weight glutenin genes from
the D-genome of a hexaploid bread wheat, Triticum aestivum L. cv Cheyenne. Nucleic
Acids Res. 17:461-462.
Anderson, O. D. and Green, F. C., 1989. The characterization and comparative analysis of
high-molecular-weight glutenin genes from genomes A and B of a hexaploid bread wheat.
Theor. Appl. Genet. 77:689-700.
Anjum, F.M. and Walker, C.E., 1991. Review on the significance of starch and protein to
wheat kemel hardness. J. Sci. Food Agric. 56: 1-13.
Autran, l-C., Lew, E. J.-L., Nimrno, C. C. and Kasarda, D. D., 1979. N terminal amino
sequencing of prolamins from wheat and related species. Nature 282:527-529.
Axford, D.W.E., McDermott, E.E. and Redman, D.G., 1979. Note on the sodium dodocyl
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